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Home » Blogs » The Mission Critical Blog » Evolving Business Models And Proven Financial Return Spur Microgrid Growth
Sally-jacquemin
Sally Jacquemin leads Siemens Digital Grid Microgrid business in North America. She identifies and drives opportunities for advanced energy management of distributed resources for large energy users such as commercial & industrial campuses, universities, federal military bases, communities, and more. She influences global R&D, marketing, strategy, and thought leadership in the Digital Grid division. Prior to joining Siemens, Sally worked for a leading technology management consulting firm in Chicago. She has her MBA from the Tepper School of Business at Carnegie Mellon University and a bachelor’s in Industrial & Operations Engineering from the University of Michigan.).
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Evolving Business Models And Proven Financial Return Spur Microgrid Growth

Microgrids are a hot topic due to several market and business drivers that include decentralized energy investment and positive financial impact of on-site power generation at data centers..

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May 16, 2016
Sally Jacquemin
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KEYWORDS data center power design / data center UPS systems / data centers
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Microgrids have certainly become one of the power industry’s “hottest” topics due to several market and business drivers that include decentralized energy investment and positive financial impact of on-site power generation. There is significant value that can be realized through microgrid deployment by looking at new operating models including intelligent software advancements and remote microgrid control.

Every five or 10 years, the power industry seems to latch onto the “hot topic” of the moment and microgrids seem to be atop any list now. Although they may have gained popularity in the past five years, the concept has been around since the dawn of electrification. The recent surge of interest in decentralized energy investment or microgrids can be traced to several different converging business drivers.

First, the positive financials of on-site generation via natural gas and solar have jump-started investment in most markets. Second, the acknowledgment of our serious dependence on energy during periods of grid outages combined with the grid’s weak physical and cyber security has given some of our forward-looking political leaders cause for alarm. Third, the energy efficiency industry is grasping for new ways to stay relevant after initial lighting, cooling, and other building-centric measures have been implemented. Advanced microgrid and renewable control solutions provide the answer for grid-scale energy optimization and efficiency when local generation can be leveraged.

The textbook definition of a microgrid is a geographically localized campus with sufficient on-site generation to support disconnecting from the local grid for a period of time greater than one day. These systems generate, distribute, and regulate the flow of electrons during periods of “islanding” from the grid, performing system operating functions similar to a governing utility. In practice, microgrids have not yet become standardized to this definition. Many different applications are emerging that require significant solution design and tailoring, further verifying the still emerging nature of the market space. In reality, the term microgrid is too limiting for the software technology that can be applied to these decentralized energy solutions. Projects that only include solar and battery, only combined heat and power (CHP), or never intend to disconnect from the broader grid can all benefit from advanced microgrid control solutions.

The advanced optimization functionality found in some microgrid supervisory control and data acquisition (SCADA) control solutions is a powerful addition to any project with on-site distributed energy, regardless of the planned microgrid functionality. This optimization of system load balancing with the most cost-efficient mix of generation is based on real-time price signals, weather forecasts and other input data. While this technology is based on industry-proven utility distribution SCADA, the optimization module has only been developed and deployed on projects within the past several years resulting in limited customer data to prove the value of investment return on control project implementations. The anticipated availability of this data within the next several years as projects mature and data is collected will jump-start investment of advanced optimization control on all decentralized energy projects, not just microgrids.

Robust financial models have also been developed that take project data such as electrical and thermal consumption, generation capacity and efficiency, local utility rates and rebate programs into account in calculating the return an advanced control solution will bring any campus environment with on-site generation. On a recent university campus project, installing a local CHP solution of several megawatts was estimated to save the university up to $1 million a year in annual savings. Installing advanced optimization or microgrid control added $200,000 to $300,000 a year in additional savings, resulting in a payback between two and four years. Any project that adds decentralized energy resources such as solar and battery easily realizes an extremely attractive return on investment for this advanced control technology.

With the anticipated increase in demand of advanced control solutions, vendor deployment models will need to adapt to support a variety of business models. The traditional software deployment model of front-end capital investment with customized configuration, training, and ongoing maintenance will need to be re-visited to support customer needs that are more nimble and flexible, with less hands-on responsibility for customer IT departments. In addition, vendors will need to provide a long-term service offering with periodic payment plans to support projects without large upfront capital resources.

There have been recently launched solutions that can be hosted remotely, offering extensive functionality at an efficient, cost effective rate structure. Reduced upfront costs, shorter project implementation timelines, and minimal ongoing IT expenses makes this deployment model attractive for customers wanting an easier, more flexible software solution rollout.

These offerings host the microgrid software in secure data centers with the local area network at the microgrid site connecting to the microgrid management software server via a secure VPN. With this model, all hardware is located and maintained at the data center while system operation is still the responsibility of the customer via a VPN connection. This model allows our customers to focus on their core business rather on hardware and software system maintenance, which software engineers will seamlessly manage.

It’s certainly emerging that the renewable and microgrid industries are starting to see beyond the “quick hit” generation asset deployment projects to design comprehensive solutions that maximize the value of advanced control, not only for text book microgrids but for any combination of on-site fossil generation, renewables and battery. More value can be captured by leveraging this technology in easy to deploy solutions that require very little upfront installation resources or ongoing maintenance, making advanced control implementations a positive move for the entire energy industry.

This article originally appeared on the IEEE website.

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Sally-jacquemin
Sally Jacquemin leads Siemens Digital Grid Microgrid business in North America. She identifies and drives opportunities for advanced energy management of distributed resources for large energy users such as commercial & industrial campuses, universities, federal military bases, communities, and more. She influences global R&D, marketing, strategy, and thought leadership in the Digital Grid division. Prior to joining Siemens, Sally worked for a leading technology management consulting firm in Chicago. She has her MBA from the Tepper School of Business at Carnegie Mellon University and a bachelor’s in Industrial & Operations Engineering from the University of Michigan.).
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